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ensuring the security, integrity, and efficiency of all active systems and services. This requires a deep understanding of system architecture and involves the expert configuration of core network services
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clinical data and machine learning algorithms. The main activities include: Data Processing: • Collection of historical patient data (demographics, clinical history, outcomes of interventions). Data cleaning
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clinical data and machine learning algorithms. The main activities include: Support for AI Model Development: • Collaborating on the training of predictive models under the supervision of the scientific team
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. They should be able to thrive in the multidisciplinary culture of INESC MN and fit in projects involving physics, microfabrication, machine learning, mechatronics, etc. and be able to communicate
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13 (5 points); Bachelor Degree classification lower than 13 (2 points); B. Knowledge of Cyber-physical Systems, Automation, CAN Communication Protocol, Machine Learning, AI, Sensor Networks
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classification lower than 13 (2 points); B. Knowledge of Cyber-physical Systems, Automation, CAN Communication Protocol, Machine Learning, AI, Sensor Networks, Hierarchical Decision and Control Systems with main
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fellowship will be involved in the execution of the following tasks: 1 - Train the metamodels using machine learning techniques; 2 - Validate the machine learning results with experimental results. The aim
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Artificial Intelligence, with an emphasis on the development of methodologies and techniques for Evolutionary Computation and Machine Learning, with an emphasis on task allocation and route planning methods
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, and visualization, time series processing, and machine learning. Sense of responsibility and ability to communicate and integrate into multidisciplinary work teams. 3. Financial component - According
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legal-labor relations or the provision of services, and the grantee does not acquire the status of worker in public functions. 12. Policy of non-discrimination and equal access: FMV-ULisboa promotes a